It is often desirable to represent information using visualizations of data, such as bar graphs, pie charts, and various other forms of visualizations. Such data visualizations are advantageously capable of conveying large amounts, and varied types, of information, in forms that are compact and convenient. Moreover, such data visualizations are versatile enough to illustrate information for audiences ranging from elementary school students to advanced, specialized users in virtually any field of endeavor.
Although data visualizations were designed specifically to convey large amounts of underlying data in a manner that is visually observable to human readers, conventional computer search techniques are often largely or completely incapable of accessing or utilizing the underlying data. For example, it is typical for document files to include a data visualization as an image file; e.g., embedded within a larger document file. Many techniques exist for searching the text within such document files, but the image file displaying the data visualization will be ignored by such techniques.
Consequently, for example, a user may submit a query to be applied across a plurality of documents for desired information using conventional techniques, and the query will not be satisfied if the desired information is included in a data visualization contained in one or more of the searched documents. Similarly, a user's search within a single document may be unsuccessful if the desired information is included within a data visualization. As a result, in these and similar scenarios, such users may be unable to benefit from the desired information, even though the desired information is included within the available document(s).